Brain function is based on the computation that occurs concurrently within and among nerve cells. At the level of the single nerve cell, information from thousands of synaptic inputs is received at the dendritic spines, where it is processed by the dendrites' specific morphology and distribution of voltage-gated ion channels. Two of our participating labs have been investigating various aspects of this Neuronal Computation, including nonlinear summation of synaptic potentials and signaling functions of dendritic action potentials. To understand these dendritic functions, it is absolutely necessary to analyze the complex interplay of structure and function. Such analysis requires computational models of the neuron incorporating both information about the neuron's structure and its distribution of ion channels. Building such models has been difficult because technical considerations have dictated that structure and function be acquired separately. Recent advances in optical imaging techniques, now allow us to acquire the structure of living nerve cells and perform multi-site recording of neuronal function during a single experiment. However, choices as of the sites for functional imaging must still be made. We propose to choose these optimal recording sites based on an on-line simulation of the nerve cell under study. Such a simulation requires that structural information be acquired, a morphological reconstruction be performed, and a compartmental model of the neuron be constructed, during the short time frame of an acute experiment. The output of the simulation will guide the functional imaging by identifying sites that will yield the most information about the process under study. Finally, the acquired functional imaging data would be incorporated into the computational model for further experiments. The goal of this project is the development of a computational and experimental framework to allow real-time mapping or functional imaging data (e.g., spatio-temporal patterns of dendritic voltages or intracellular ion) to neuronal structure, during the very limited duration of an acute experiment. In order to accomplish this goal, the research objectives of this proposal are the following: . To develop the theoretical framework and computational techniques for on-line, robust, and accurate morphological reconstruction of a fluorescently labeled live nerve cell from stack of optical sections obtained using non-invasive structural imaging. . To predict on-line a nerve cell's behavior using the reconstructed morphology and a priori knowledge regarding the distribution of ion channels embodied in a compartmental model. . To guide functional imaging based on predictions of the model and the reconstructed morphology. . To optimize the computational model of the neuron by minimizing error between the predictions and the data acquired during functional imaging. The impact of the proposed project is in its enhancement of the data acquisition process, particularly in optimizing the value of multi-site optical recordings, and in the focused and directed incorporation of data into quantitative computational models of nerve cells. Our computational and experimental framework will guide the efficient design of experiments and the generation of new hypotheses that can help reveal functional mechanisms underlying both normal and diseased states of the nervous system, both for us and for other researchers. The successful completion of the proposed research requires input from neuroscience, bio-imaging, biophysics, and computer science. Thus, our project demands collaboration and complementary expertise for its success - our team is uniquely suited to accomplish this challenge and also to attract and train excellent students.